# cell type annotations
display_df(cell_df_complete)

# organ annotations
display_df(organ_df_complete)

# stage annotations
display_df(stage_df_complete)

experiment_id = "SRP461573"

path_to_create_exp_script = "/Users/scarsana/Desktop/git/scRNA-Seq/scripts/Create_ExpLib_tables.py" 
path_to_barcodes_script = "/Users/scarsana/Desktop/git/scRNA-Seq/scripts/create_scRNASeq_barcode_v2.py"
experiment_type = "scRNA"

path_to_output_main = "/Users/scarsana/Desktop/git/expression-annotations/Notebooks/scRNA/" 
path_to_output = "{}{}/".format(path_to_output_main, experiment_id)
library_path_from_script = "{}scRNASeqLibrary_{}.tsv".format(path_to_output, experiment_id)
experiment_path_from_script = "{}scRNASeqExperiment_{}.tsv".format(path_to_output, experiment_id)
barcode_path = "{}scRNASeq_barcode_{}.tsv".format(path_to_output, experiment_id)
barcode_to_add_path = "{}complete_scRNASeq_barcode_{}.tsv".format(path_to_output, experiment_id)
library_to_add_path = "{}complete_scRNASeqLibrary_{}.tsv".format(path_to_output, experiment_id)
experiment_to_add_path = "{}complete_RNASeqExperiment_{}.tsv".format(path_to_output, experiment_id)
script_file = "{}.ipynb".format(experiment_id)
commit_message_exp = '"adding annotated scRNA experiment {}"'.format(experiment_id)
commit_message_py = '"adding annotation files for {} to notebook folder"'.format(experiment_id)



## to add to git
path_to_git_annotations = "/Users/scarsana/Desktop/git/expression-annotations/scRNA_Seq/"
git_library_path = "{}scRNASeqLibrary_merged.tsv".format(path_to_git_annotations)
git_experiment_path = "{}scRNASeqExperiment.tsv".format(path_to_git_annotations)
git_barcode_path = "{}scRNASeq_barcode_{}.tsv".format(path_to_git_annotations, experiment_id)

## columns
library_cols = ['#libraryId', 'experimentId', 'platform', 'SRSId', 'anatId', 'anatName', 'cellTypeId', 'cellTypeName', 'stageId', 'stageName', 'url_GSM', 'infoOrgan', 'infoCellType_abInitio', 'infoCellType_inferred', 'clusterId', 'clusterName', 'infoStage', 'anatAnnotationStatus', 'cellTypeAnnotationStatus', 'stageAnnotationStatus', 'sex', 'strain', 'genotype', 'speciesId', 'RNAseqTags', 'protocol', 'protocolType', 'lib_name', 'sampleName', 'comment', 'condition', 'annotatorId', 'lastModificationDate']
barcode_cols = ['barcode', 'cluster', 'library', 'experiment', 'tissue', 'cell_type', 'anatId_a_posteriori', 'anatName_a_posteriori', 'anat_a_posteriori_annotationStatus', 'cellTypeId', 'cellTypeName', 'cellTypeAnnotationStatus', 'name_Library', 'comments']

## annotation sheet paths (maybe make these into their own folder)
annotation_files_path = "{}annotation_files/".format(path_to_output)
import os
if not os.path.exists(annotation_files_path):
    os.makedirs(annotation_files_path)

info_anat_path = "{}info_anat.tsv".format(annotation_files_path)
info_anat_complete_path = "{}info_anat_complete.tsv".format(annotation_files_path)
info_stage_path = "{}info_dev_stage.tsv".format(annotation_files_path)
info_stage_complete_path = "{}info_dev_stage_complete.tsv".format(annotation_files_path)
info_celltype_path = "{}info_celltype.tsv".format(annotation_files_path)
info_celltype_complete_path = "{}info_celltype_complete.tsv".format(annotation_files_path)

## barcode file & matching library names - 10X only
path_to_barcode_file = "{}barcode_{}.tsv".format(path_to_output, experiment_id)
lib_names_path = "{}matching_lib_names_{}.tsv".format(path_to_output, experiment_id)

import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import pandas as pd
import numpy as np
from IPython.display import display, HTML
import csv
import scanpy as sc
import gc

# displays df with the scrollbar next to the DataFrame
def display_df(df):
    pd.set_option("display.max_rows", None)
    pd.set_option("display.max_columns", None)
    display(HTML("<div style='height: 200px; overflow: auto; width: fit-content'>" +
        df.style.to_html(index=False) + "</div>"))

# function that compares two columns in a dataframe and tells you which ones are not equal (case insensitive)
def compare_columns(df, col1, col2, return_col):
    compare_return = df[col1].str.lower() != df[col2].str.lower()  
    df.loc[compare_return, return_col] 
    if not any(compare_return):
        print("The two columns are equal (case insensitive)")
    else:
        print("The following rows are not equal: ")
        print(df.loc[compare_return, return_col])

# fixes formatting of file to match libreoffice settings/historic file format
def update_format(path):
    with open(path, 'r') as file:
        filedata = file.read()
    # Replace the target string
    filedata = filedata.replace("\t\"\"", "\t")
    # Write the file out again
    with open(path, 'w') as file:
        file.write(filedata)

# checks for duplicate values in a specific column and prints those values + the corresponding library id
def dup_check(df, column):
    duplicateCheck = df.duplicated(subset=[column], keep=False)
    duplicateCheck.sort_values(inplace=True)
    if duplicateCheck.unique().any() == False:
        print("no duplicate values in " + column)
    elif duplicateCheck.unique().any() == True and column != '#libraryId':
        dups = df[duplicateCheck].loc[:,['#libraryId', column]]
        df_dups = pd.DataFrame(dups)
        df_dups.sort_values(inplace=True, by=column)
        print(df_dups)
    elif duplicateCheck.unique().any() == True and column == '#libraryId':
        print(df[duplicateCheck].loc[:,['#libraryId']])

# prints all unique values in a specific column
def unique_sorted(df, column):
    unique = df[column].unique()
    unique.sort()
    print(unique)

pd.set_option('display.max_rows', 500)

/var/folders/b5/crkp117d43q5mcndnwlrww3w0000gn/T/ipykernel_70561/3788529765.py:3: DeprecationWarning: 
Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),
(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)
but was not found to be installed on your system.
If this would cause problems for you,
please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466
        
  import pandas as pd

# h5ad file metadata access
adata = sc.read("MRCA-scRNA-seq of the mouse retina-all cells.h5ad")
metadata = adata.obs

# check unique accessions in this file
meta_accessions = metadata[['accession']]
unique_meta_accessions = meta_accessions.drop_duplicates().sort_values(by = 'accession')
unique_meta_accessions

# start with new data from this study only
only_GSE243413 = metadata[metadata["accession"] == "GSE243413"]

# check samples to compare with library names from SRA
GSE243413_samples = only_GSE243413[['sampleid']]
unique_GSE243413_samples = GSE243413_samples.drop_duplicates().sort_values(by = 'sampleid')
unique_GSE243413_samples
# there are more samples in SRA than here, will need to find a way to match them correctly

# take a look at annotations
GSE243413_celltype = only_GSE243413[['author_cell_type', 'majorclass','cell_type']]
unique_GSE243413_celltype = GSE243413_celltype.drop_duplicates().sort_values(by = 'author_cell_type')
unique_GSE243413_celltype

adata_amacrine = sc.read("MRCA- scRNA-seq of the mouse retina - amacrine cell subclass.h5ad")
metadata_amacrine = adata_amacrine.obs

adata_bipolar = sc.read("MRCA- scRNA-seq of the mouse retina - bipolar cell subclass.h5ad")
metadata_bipolar = adata_bipolar.obs

adata_RGC = sc.read("MRCA- scRNA-seq of the mouse retina - RGC subclass.h5ad")
metadata_RGC = adata_RGC.obs

GSE243413_amacrine = metadata_amacrine[metadata_amacrine["accession"] == "GSE243413"]
GSE243413_bipolar = metadata_bipolar[metadata_bipolar["accession"] == "GSE243413"]
GSE243413_RGC = metadata_RGC[metadata_RGC["accession"] == "GSE243413"]

# check samples to compare with library names from SRA
amacrine_samples = GSE243413_amacrine[['sampleid']]
unique_amacrine_samples = amacrine_samples.drop_duplicates().sort_values(by = 'sampleid')
unique_amacrine_samples

# check samples to compare with library names from SRA
bipolar_samples = GSE243413_bipolar[['sampleid']]
unique_bipolar_samples = bipolar_samples.drop_duplicates().sort_values(by = 'sampleid')
unique_bipolar_samples

# check samples to compare with library names from SRA
RGC_samples = GSE243413_RGC[['sampleid']]
unique_RGC_samples = RGC_samples.drop_duplicates().sort_values(by = 'sampleid')
unique_RGC_samples

# take a look at annotations
amacrine_celltype = GSE243413_amacrine[['author_cell_type', 'celltype_resolution', 'AC_subclass','cell_type']]
unique_amacrine_celltype = amacrine_celltype.drop_duplicates().sort_values(by = 'celltype_resolution')
unique_amacrine_celltype

# take a look at annotations
bipolar_celltype = GSE243413_bipolar[['author_cell_type', 'cell_type']]
unique_bipolar_celltype = bipolar_celltype.drop_duplicates().sort_values(by = 'cell_type')
unique_bipolar_celltype

# take a look at annotations
RGC_celltype = GSE243413_RGC[['author_cell_type', 'celltype_resolution','cell_type']]
unique_RGC_celltype = RGC_celltype.drop_duplicates().sort_values(by = 'author_cell_type')
unique_RGC_celltype

platform_GSE243413 = only_GSE243413[['sampleid', 'library_platform']]
unique_platform_GSE243413 = platform_GSE243413.drop_duplicates().sort_values(by = 'library_platform')
unique_platform_GSE243413

# check samples to compare with library names from SRA
GSE243413_samples = only_GSE243413[['sampleid']]
unique_GSE243413_samples = GSE243413_samples.drop_duplicates().sort_values(by = 'sampleid')
unique_GSE243413_samples

only_GSE243413['sample_full'] = only_GSE243413['sampleid']

/var/folders/b5/crkp117d43q5mcndnwlrww3w0000gn/T/ipykernel_70561/1917016230.py:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  only_GSE243413['sample_full'] = only_GSE243413['sampleid']

only_GSE243413.index.name = 'barcodes'
only_GSE243413.reset_index(inplace=True)

# checking how many rows might corresponnd to each SRA sample, and how to split them accurately  
only_GSE243413[only_GSE243413['barcodes'].astype(str).str.contains('10x_retina0315CD73NDRv2_A|10x_retina0315CD73NDRv2_C|10x_retina0315CD73NDRv2_G|10x_retina0315CD73NDRv2_T')]

only_GSE243413['sample_full'] = only_GSE243413.sample_full.astype(str)

/var/folders/b5/crkp117d43q5mcndnwlrww3w0000gn/T/ipykernel_70561/1978259889.py:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  only_GSE243413['sample_full'] = only_GSE243413.sample_full.astype(str)

only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x_retina0315CD73NDRv2_A|10x_retina0315CD73NDRv2_C|10x_retina0315CD73NDRv2_G|10x_retina0315CD73NDRv2_T'), 'sample_full'] = '10x_retina0315CD73NDRv2 reaction 1'

only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x_retina0315CD73NDRv2_1'), 'sample_full'] = '10x_retina0315CD73NDRv2 reaction 2'
only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x_retina0315CD73NDRv2_2'), 'sample_full'] = '10x_retina0315CD73NDRv2 reaction 3'
only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x_retina0315CD73NDRv2_3'), 'sample_full'] = '10x_retina0315CD73NDRv2 reaction 4'
only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x_retina0315CD73NDRv2_4'), 'sample_full'] = '10x_retina0315CD73NDRv2 reaction 5'

only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x_retina_WT_4M_1'), 'sample_full'] = '10x_retina_WT_4M reaction 1'
only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x_retina_WT_4M_2'), 'sample_full'] = '10x_retina_WT_4M reaction 2'

only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x3_Ms_WT_P180_1'), 'sample_full'] = '10x3_Ms_WT_P180 reaction 1'
only_GSE243413.loc[only_GSE243413.barcodes.str.contains('10x3_Ms_WT_P180_2'), 'sample_full'] = '10x3_Ms_WT_P180 reaction 2'

check_GSE243413 = only_GSE243413[['sampleid', 'sample_full']]
unique_check_GSE243413 = check_GSE243413.drop_duplicates().sort_values(by = 'sample_full')
unique_check_GSE243413

list(only_GSE243413)

['barcodes',
 'nCount_RNA',
 'nFeature_RNA',
 'percent.mt',
 'pANN',
 'sampleid',
 'subclass_label',
 'majorclass',
 'author_cell_type',
 'age',
 'gender',
 'reference',
 'accession',
 'sample_note',
 'development_stage_ontology_term_id',
 'tissue_ontology_term_id',
 'assay_ontology_term_id',
 'disease_ontology_term_id',
 'donor_id',
 'organism_ontology_term_id',
 'self_reported_ethnicity_ontology_term_id',
 'sex_ontology_term_id',
 'suspension_type',
 'tissue_type',
 'library_platform',
 'cell_type_ontology_term_id',
 'is_primary_data',
 'cell_type',
 'assay',
 'disease',
 'organism',
 'sex',
 'tissue',
 'self_reported_ethnicity',
 'development_stage',
 'observation_joinid',
 'sample_full']

barcodes_from_author = only_GSE243413[['barcodes', 'sampleid', 'sample_full', 'library_platform', 'gender', 'age', 'development_stage', 'development_stage_ontology_term_id', 'tissue', 'tissue_ontology_term_id', 'author_cell_type', 'majorclass','cell_type', 'cell_type_ontology_term_id']]

barcodes_from_author.to_csv("barcode_SRP461573.tsv", sep="\t", index=False, quoting=csv.QUOTE_ALL)

! python3 $path_to_create_exp_script $experiment_id $path_to_output $experiment_type

/Users/scarsana/Desktop/git/scRNA-Seq/scripts/Create_ExpLib_tables.py:97: SyntaxWarning: invalid escape sequence '\('
  all_protoc = [w.replace('(', '\(') for w in all_protoc]
/Users/scarsana/Desktop/git/scRNA-Seq/scripts/Create_ExpLib_tables.py:98: SyntaxWarning: invalid escape sequence '\)'
  all_protoc = [w.replace(')', '\)') for w in all_protoc] 
/Users/scarsana/Desktop/git/scRNA-Seq/scripts/Create_ExpLib_tables.py:11: DeprecationWarning: 
Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),
(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)
but was not found to be installed on your system.
If this would cause problems for you,
please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466
        
  import pandas as pd
Be patient, it may take a few minutes.
0it [00:00, ?it/s]
0 samples dont have attributes, try to find them somewhere else
0it [00:00, ?it/s]
0 samples dont have attributes

library = pd.read_csv(library_path_from_script, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(library)

infoOrgan = library['infoOrgan'].drop_duplicates().sort_values()
organ_df = pd.DataFrame(infoOrgan)
organ_df = organ_df.reindex(columns=[*organ_df.columns.tolist(), 'notes_anat', 'anatId_', 'anatName_', 'anatAnnotationStatus_', 'infoOrgan_new', 'comment_anat'], fill_value="")
organ_df.to_csv(info_anat_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
if not os.path.exists(info_anat_complete_path): 
    organ_df.to_csv(info_anat_complete_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

# options for anatAnnotationStatus: perfect match, missing child term, other

organ_df_complete = pd.read_csv(info_anat_complete_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(organ_df_complete)

library = library.merge(organ_df_complete, left_on='infoOrgan', right_on='infoOrgan')

library['anatId'] = library['anatId_'].values
library['anatName'] = library['anatName_'].values
library['anatAnnotationStatus'] = library['anatAnnotationStatus_'].values

## optional - update infoOrgan, add anat-specific comments 
#library['infoOrgan'] = library['infoOrgan_new'].values
#library['comment'] = library[['comment', 'comment_anat']].agg(' '.join, axis=1)

# reformat, save progress
library = library[library_cols]
display_df(library)
library.to_csv(library_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

infoStage = library['infoStage'].drop_duplicates().sort_values()
stage_df = pd.DataFrame(infoStage)
stage_df = stage_df.reindex(columns=[*stage_df.columns.tolist(), 'notes_stage', 'stageId_', 'stageName_', 'stageAnnotationStatus_', 'infoStage_new','comment_stage'], fill_value="")
stage_df.to_csv(info_stage_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
if not os.path.exists(info_stage_complete_path): 
    stage_df.to_csv(info_stage_complete_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

# options for stageAnnotationStatus: perfect match, missing child term, other

barcode_subset = pd.read_csv('barcode_SRP461573.tsv', sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

# take a look at annotations from h5ad file
dev_subset = barcode_subset[['sampleid', 'age','development_stage', 'development_stage_ontology_term_id']]
unique_dev_subset = dev_subset.drop_duplicates().sort_values(by = 'age')
unique_dev_subset

stage_df_complete = pd.read_csv(info_stage_complete_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(stage_df_complete)

library = library.merge(stage_df_complete, left_on='infoStage', right_on='infoStage')

library['stageId'] = library['stageId_'].values
library['stageName'] = library['stageName_'].values
library['stageAnnotationStatus'] = library['stageAnnotationStatus_'].values

## optional - update infoOrgan, add anat-specific comments 
library['infoStage'] = library['infoStage_new'].values
#library['comment'] = library[['comment', 'comment_stage']].agg(' '.join, axis=1)

# reformat, save progress
library = library[library_cols]
display_df(library)
library.to_csv(library_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

library.loc[library["sex"] == "male", "sex"] = "M"
#library.loc[library["sex"] == "female", "sex"] = "F"

# strain specified in paper's methods 
library.loc[:,'strain'] = 'C57BL/6J'

# this is specified in SRA, just removing the dash (-) to match our current annotations
library.loc[:,'genotype'] = 'wild type'

#library.loc[:,'speciesId'] = ''

# view
display_df(library)

unique_lib = library[['lib_name']]
unique_lib_samples = unique_lib.drop_duplicates().sort_values(by = 'lib_name')
unique_lib_samples

unique_platform_GSE243413

v2_libs = ['10x_Retina0313v2', '10x_retina0315CD73NDRv2 reaction 1', '10x_retina0315CD73NDRv2 reaction 2', '10x_retina0315CD73NDRv2 reaction 3', '10x_retina0315CD73NDRv2 reaction 4', '10x_retina0315CD73NDRv2 reaction 5', '10x_retina0315CD73Nv2', 'RGC_3_AC', 'RGC_live_AC']

library.loc[library['lib_name'].isin(v2_libs), 'protocol'] = '10X Genomics V2'
library.loc[~library['lib_name'].isin(v2_libs), 'protocol'] = '10X Genomics V3'

platform_lib = library[['protocol', 'lib_name']]
unique_platform_lib = platform_lib.drop_duplicates().sort_values(by = 'protocol')
unique_platform_lib

# making these variables because we use them again in the experiment file
# usually 10X Genomics V1/V2/V3/V3.1, Smart-seq, Smart-seq2
# need confirmation from authors, seems split between V2 and V3 despite the methods suggesting different
#my_protocol = ''
# Full-length or 3'end or 5'end
my_protocolType = "3'end"

#library.loc[:,'protocol'] = my_protocol
library.loc[:,'protocolType'] = my_protocolType
# scRNA-seq, Sn-scRNA-seq
library.loc[:,'RNAseqTags'] = 'scRNA-seq'

# view
display_df(library)

# ex. control, diet, light, reproductive capacity, time post mortem, time post feeding, 
# exercise details, menstruation, personality, litter size 
general_comment = ', not clear if platform is 10X v2 or v3 but annotated based on h5ad file, review if pipeline has errors'
library['comment'] = library['condition'].values
library['comment'] =  library['comment'].astype(str) + general_comment
#library[['comment', general_comment]].agg(', '.join, axis=1)
display_df(library)

library.loc[:,'condition'] = ''


# view
display_df(library)

library.loc[:,'annotatorId'] = 'SAC'
library.loc[:,'lastModificationDate'] = '2024-12-12'

# view
display_df(library)

#library.loc[:,'comment'] = ''

library_file_complete = library[library_cols]

library_file_complete.to_csv(library_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

# view
display_df(library_file_complete)

barcode_column = "barcodes"
library_column = "sample_full"
cell_type_column = "author_cell_type"

! python3 $path_to_barcodes_script $path_to_output --scRNASeqLibrary $library_to_add_path --barcode_file $path_to_barcode_file --barcode_col $barcode_column --libName_col $library_column --cellType_col $cell_type_column --ignore_check --no_additional_file

/Users/scarsana/Desktop/git/scRNA-Seq/scripts/create_scRNASeq_barcode_v2.py:10: DeprecationWarning: 
Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),
(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)
but was not found to be installed on your system.
If this would cause problems for you,
please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466
        
  import pandas as pd
There are 22 unique libraries in scRNASeqLibrary.tsv table
There are 22 unique libraries in the barcode table provided
Be extra careful if not same number of libraries in both tables, always manually check the matching names in 'matching_lib_names.tsv' table output
100%|█████████████████████████████████████████| 22/22 [00:00<00:00, 4063.53it/s]
                              name_Library                        new_lib_name
22990                       10x3_Ms_WT_P40                      10x3_Ms_WT_P40
66839                  10x_Retina0426Cd73N                 10x_Retina0426Cd73N
121435               10x_retina0315CD73Nv2               10x_retina0315CD73Nv2
46095                  10x_Retina0423Cd73N                 10x_Retina0423Cd73N
78604                  10x_Retina0426Cd73N                 10x_Retina0426Cd73N
96930   10x_retina0315CD73NDRv2 reaction 3  10x_retina0315CD73NDRv2 reaction 3
119926               10x_retina0315CD73Nv2               10x_retina0315CD73Nv2
82643   10x_retina0315CD73NDRv2 reaction 2  10x_retina0315CD73NDRv2 reaction 2
160609               10x_retina0401CD73Nv3               10x_retina0401CD73Nv3
17093           10x3_Ms_WT_P180 reaction 2          10x3_Ms_WT_P180 reaction 2
148621               10x_retina0401CD73Nv3               10x_retina0401CD73Nv3
78708                  10x_Retina0426Cd73N                 10x_Retina0426Cd73N
59407                  10x_Retina0423Cd73N                 10x_Retina0423Cd73N
83094   10x_retina0315CD73NDRv2 reaction 2  10x_retina0315CD73NDRv2 reaction 2
37498                    10x3_Ms_WT_PBS_2L                   10x3_Ms_WT_PBS_2L
141704               10x_retina0401CD73Nv3               10x_retina0401CD73Nv3
19759           10x3_Ms_WT_P180 reaction 1          10x3_Ms_WT_P180 reaction 1
152110               10x_retina0401CD73Nv3               10x_retina0401CD73Nv3
169519               10x_retina0401CD73Nv3               10x_retina0401CD73Nv3
24473                       10x3_Ms_WT_P40                      10x3_Ms_WT_P40
0 libraries dont have any barcodes !!
the following libraries don't have any barcodes: set()

lib_names = pd.read_csv(lib_names_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
display_df(lib_names)

barcode_file = pd.read_csv(barcode_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

cell_type = barcode_file['cell_type'].drop_duplicates().sort_values()
cell_df = pd.DataFrame(cell_type)
cell_df = cell_df.reindex(columns=[*cell_df.columns.tolist(), 'notes_cell', 'cellTypeId_', 'cellTypeName_', 'cellTypeAnnotationStatus_', 'cell_type_new','comment_cell'], fill_value="")
cell_df.to_csv(info_celltype_path, sep="\t", index=False)
if not os.path.exists(info_celltype_complete_path): 
    cell_df.to_csv(info_celltype_complete_path, sep="\t", index=False)

# options for cellTypeAnnotationStatus: perfect match, missing child term, other

author_barcode_file = pd.read_csv(path_to_barcode_file, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
author_celltype = author_barcode_file[['author_cell_type', 'majorclass','cell_type', 'cell_type_ontology_term_id']]
unique_author_celltype = author_celltype.drop_duplicates().sort_values(by = ['majorclass', 'author_cell_type'])
print(np.shape(unique_author_celltype))
unique_author_celltype

(128, 4)

cell_df_complete = pd.read_csv(info_celltype_complete_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
#display_df(cell_df_complete)

compare_cell_annotations = cell_df_complete.merge(unique_author_celltype, left_on='cell_type', right_on='author_cell_type')

compare_cell_annotations

compare_cell_annotations.dtypes

cell_type_x                   object
notes_cell                    object
cellTypeId_                   object
cellTypeName_                 object
cellTypeAnnotationStatus_     object
cell_type_new                 object
comment_cell                  object
author_cell_type              object
majorclass                    object
cell_type_y                   object
cell_type_ontology_term_id    object
dtype: object

compare_cell_annotations['match'] = compare_cell_annotations['cellTypeId_'].astype(str).isin(compare_cell_annotations['cell_type_ontology_term_id'].astype(str))

display_df(compare_cell_annotations.loc[compare_cell_annotations['match']==False])

barcode_file = barcode_file.merge(cell_df_complete, left_on='cell_type', right_on='cell_type')

barcode_file['cellTypeId'] = barcode_file['cellTypeId_'].values
barcode_file['cellTypeName'] = barcode_file['cellTypeName_'].values
barcode_file['cellTypeAnnotationStatus'] = barcode_file['cellTypeAnnotationStatus_'].values

# optional - update cell type name and add comments
#barcode_file['cell_type'] = barcode_file['cell_type_new'].values
#barcode_file['comment'] = barcode_file[['comment', 'comment_cell']].agg(' '.join, axis=1)

barcode_file_complete = barcode_file[barcode_cols]
display_df(barcode_file_complete)
barcode_file_complete.to_csv(barcode_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

experiment = pd.read_csv(experiment_path_from_script, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
experiment.head()

library_to_add = pd.read_csv(library_to_add_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

# this will give you the number of rows in the complete library file 
# this should be the number of annotated libraries
ann_lib = len(library_to_add.index)
len(library_to_add.index)

22

# partial or total
experiment.loc[:,'experimentStatus'] = 'total'
# scRNA-seq, Sn-scRNA-seq for both we put: 'Sn-scRNA-seq, scRNA-seq'
experiment.loc[:,'RNAseqTags'] = 'scRNA-seq'


# see above cell, also can add as free text
experiment.loc[:,'numberOfAnnotatedLibraries'] = ann_lib

# these variables should already exist from above but if not can just add as free text
experiment.loc[:,'protocol'] = '10X Genomics V2, 10X Genomics V3'
experiment.loc[:,'protocolType'] = my_protocolType

experiment.head()

experiment.loc[:,'GSE'] = 'GSE243413'
#experiment.loc[:,'Bioproject'] = '' 
experiment.loc[:,'PMID'] = '38812536'
experiment.loc[:,'reference_url'] = 'https://pmc.ncbi.nlm.nih.gov/articles/PMC11134544/'
experiment.loc[:,'DOI'] = '10.1016/j.isci.2024.109916'
experiment.loc[:,'xrefs'] = '38328114[PMID]'

experiment.head()

experiment.loc[:,'comment'] = 'not clear if platform is 10X v2 or v3 but annotated based on h5ad file, review if pipeline has errors'

experiment.head()

experiment.to_csv(experiment_to_add_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)

library_to_add = pd.read_csv(library_to_add_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
experiment_to_add = pd.read_csv(experiment_to_add_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

# pull from git and pull in library/experiment file
! git pull
git_library = pd.read_csv(git_library_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
git_experiment = pd.read_csv(git_experiment_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)

# library file
if set(library_to_add.columns) == set(git_library.columns):
    print('The columns in the library file match')
else:
    print('The columns in the library file DO NOT MATCH')

# experiment file
if set(experiment_to_add.columns) == set(git_experiment.columns):
    print('The columns in the experiment file match')
else:
    print('The columns in the experiment file DO NOT MATCH')


# maybe to make this something more like "COLUMNS GOOD - LIBRARY" and "COLUMNS BAD - EXPERIMENT"

Already up to date.
The columns in the library file match
The columns in the experiment file match

library_git_plus_new = pd.concat([git_library, library_to_add], ignore_index = True, sort = False)
library_git_plus_new.tail(n=25)

experiment_git_plus_new = pd.concat([git_experiment, experiment_to_add], ignore_index = True, sort = False)
experiment_git_plus_new.tail(n=5)

# 10X only
barcode_file_for_git = pd.read_csv(barcode_to_add_path, sep='\t', index_col=False, keep_default_na=False, na_values=['NULL','null', 'nan','NaN', " "], dtype=object)
barcode_file_for_git.head(20)

! git pull

Already up to date.

library_git_plus_new.to_csv(git_library_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
update_format(git_library_path)
experiment_git_plus_new.to_csv(git_experiment_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
update_format(git_experiment_path)

# 10X only
barcode_file_for_git.to_csv(git_barcode_path, sep="\t", index=False, quoting=csv.QUOTE_ALL)
update_format(git_barcode_path)

! git status

On branch develop
Your branch is up to date with 'origin/develop'.

Changes not staged for commit:
  (use "git add <file>..." to update what will be committed)
  (use "git restore <file>..." to discard changes in working directory)
	modified:   ../../../scRNA_Seq/scRNASeqExperiment.tsv
	modified:   ../../../scRNA_Seq/scRNASeqLibrary_merged.tsv

Untracked files:
  (use "git add <file>..." to include in what will be committed)
	../../bulk/NCBI_output/
	./
	../../../scRNA_Seq/scRNASeq_barcode_SRP461573.tsv

no changes added to commit (use "git add" and/or "git commit -a")

# 10X (barcode file)
! git add $git_experiment_path $git_library_path $git_barcode_path

! git status

On branch develop
Your branch is up to date with 'origin/develop'.

Changes to be committed:
  (use "git restore --staged <file>..." to unstage)
	modified:   ../../../scRNA_Seq/scRNASeqExperiment.tsv
	modified:   ../../../scRNA_Seq/scRNASeqLibrary_merged.tsv
	new file:   ../../../scRNA_Seq/scRNASeq_barcode_SRP461573.tsv

Untracked files:
  (use "git add <file>..." to include in what will be committed)
	../../bulk/NCBI_output/
	./

! git commit -m $commit_message_exp

[develop c7632f7] adding annotated scRNA experiment SRP461573
 3 files changed, 189216 insertions(+)
 create mode 100644 scRNA_Seq/scRNASeq_barcode_SRP461573.tsv

! git push

Enumerating objects: 10, done.
Counting objects: 100% (10/10), done.
Delta compression using up to 12 threads
Compressing objects: 100% (6/6), done.
Writing objects: 100% (6/6), 1.18 MiB | 5.27 MiB/s, done.
Total 6 (delta 4), reused 0 (delta 0), pack-reused 0
remote: 
remote: ========================================================================
remote: 
remote:      Hello all, Gitlab will be unavailable 2024-12-13 from 09:00 to
remote:       10:00 due to security maintenance works. Please refrain from
remote:      logging in during this time. Thank you for your understanding
remote: 
remote: ========================================================================
remote: 
remote: 
remote: To create a merge request for develop, visit:
remote:   https://gitlab.sib.swiss/Bgee/expression-annotations/-/merge_requests/new?merge_request%5Bsource_branch%5D=develop
remote: 
To https://gitlab.sib.swiss/Bgee/expression-annotations.git
   de5db09..c7632f7  develop -> develop

! git status

! git add $path_to_output

! git commit -m $commit_message_py

! git push

	cell_type	notes_cell	cellTypeId_	cellTypeName_	cellTypeAnnotationStatus_
0	10_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
1	11_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
2	12_ooDS_NT	transient ON-OFF response, DSGC (Vaney, Sivyer, Taylor 2012)	CL:0000740	retinal ganglion cell	missing child term
3	13_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
4	14_ooDS_Cck		CL:0000740	retinal ganglion cell	missing child term
5	15_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
6	16_ooDS_DV	transient ON-OFF response, DSGC (Vaney, Sivyer, Taylor 2012), DV is for dorsal ventral	CL:0000740	retinal ganglion cell	missing child term
7	17_Tbr1_S1	defined by expression of the transcription factor Tbr1	CL:0000740	retinal ganglion cell	missing child term
8	18_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
9	19_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
10	1_W3D1.1	defined by the transgene TYW3, dendritic lamination in the middle third of the IPL; D is for dim (W3D)	CL:0000740	retinal ganglion cell	missing child term
11	20_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
12	21_Tbr1_S2	defined by expression of the transcription factor Tbr1	CL:0000740	retinal ganglion cell	missing child term
13	22_M5	ipRGCs	CL:0003034	M5 retinal ganglion cell	perfect match
14	23_W3D2	defined by the transgene TYW3, dendritic lamination in the middle third of the IPL; D is for dim (W3D)	CL:0000740	retinal ganglion cell	missing child term
15	24_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
16	25_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
17	26_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
18	27_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
19	28_FmidiOFF	OFF, DSGC, color-opponent (Kim et al. 2008, Joesch & Meister 2016), from table S1 PMID 31784286	CL:4023033	OFF retinal ganglion cell	missing child term
20	29_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
21	2_W3D1.2	defined by the transgene TYW3, dendritic lamination in the middle third of the IPL; D is for dim (W3D)	CL:0000740	retinal ganglion cell	missing child term
22	30_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
23	31_M2	ipRGC, sustained ON response, NSGC (Bae et al. 2018)	CL:0003029	M2 retinal ganglion cell	perfect match
24	32_F_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
25	33_M1	ipRGC, weak light evoked response (Bae et al 2018), from table S1 PMID 31784286	CL:0003028	M1 retinal ganglion cell	perfect match
26	34_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
27	35_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
28	36_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
29	37_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
30	38_FmidiON	transient ON response, NSGC (Rousso et al. 2016), from table S1 PMID 31784286	CL:4023032	ON retinal ganglion cell	missing child term
31	3_FminiON	transient ON response, DSGC (Rousso et al. 2016), from table S1 PMID 31784286	CL:4023032	ON retinal ganglion cell	missing child term
32	40_M1dup	M1 duplicate where M1 is ipRGC, weak light evoked response (Bae et al 2018), from table S1 PMID 31784286	CL:0003028	M1 retinal ganglion cell	other
33	41_AlphaONT	alpha RGC, likely on-transient type	CL:0004117	retinal ganglion cell A	missing child term
34	43_AlphaONS	alpha RGC, likely on-sustained type	CL:0004117	retinal ganglion cell A	missing child term
35	44_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
36	4_FminiOFF	transient OFF response, DSGC (On-Off direction-selective) (Rousso et al. 2016), from table S1 PMID 31784286	CL:4023033	OFF retinal ganglion cell	missing child term
37	5_J-RGC	overexpression of Jam2 per PMID 31784286, JamB retinal ganglion cells	CL:0000740	retinal ganglion cell	missing child term
38	6_W3B	defined by the transgene TYW3, dendritic lamination in the middle third of the IPL; B is for bright (W3B)	CL:0000740	retinal ganglion cell	missing child term
39	7_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
40	8_Novel	novel RGC subtypes get general RGC ontology label	CL:0000740	retinal ganglion cell	perfect match
41	9_Tbr1_Novel	defined by expression of the transcription factor Tbr1	CL:0000740	retinal ganglion cell	missing child term
42	AC	amacrine cells	CL:0000561	amacrine cell	perfect match
43	AC_1	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
44	AC_10	nGnG	CL:0000561	amacrine cell	missing child term
45	AC_11	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
46	AC_12	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
47	AC_13	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
48	AC_14	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
49	AC_15	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
50	AC_16	Both (Glycinergic and GABAergic)	CL:0000561	amacrine cell	missing child term
51	AC_17	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
52	AC_18	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
53	AC_19	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
54	AC_2	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
55	AC_20	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
56	AC_21	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
57	AC_22	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
58	AC_23	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
59	AC_24	nGnG	CL:0000561	amacrine cell	missing child term
60	AC_25	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
61	AC_26	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
62	AC_27	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
63	AC_28	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
64	AC_29	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
65	AC_3	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
66	AC_30	nGnG	CL:0000561	amacrine cell	missing child term
67	AC_31	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
68	AC_32	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
69	AC_33	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
70	AC_34	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
71	AC_35	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
72	AC_36	nGnG	CL:0000561	amacrine cell	missing child term
73	AC_37	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
74	AC_38	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
75	AC_39	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
76	AC_4	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
77	AC_40	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
78	AC_41	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
79	AC_42	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
80	AC_43	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
81	AC_44	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
82	AC_45	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
83	AC_46	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
84	AC_47	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
85	AC_48	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
86	AC_5	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
87	AC_50	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
88	AC_51	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
89	AC_52	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
90	AC_54	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
91	AC_55	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
92	AC_56	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
93	AC_57	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
94	AC_58	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
95	AC_59	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
96	AC_6	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
97	AC_60	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
98	AC_61	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
99	AC_63	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
100	AC_7	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
101	AC_8	GABAergic	CL:4030027	GABAergic amacrine cell	perfect match
102	AC_9	Glycinergic	CL:4030028	glycinergic amacrine cell	perfect match
103	BC	bipolar cell	CL:0000748	retinal bipolar neuron	perfect match
104	BC1A		CL:0000753	type 1 cone bipolar cell (sensu Mus)	missing child term
105	BC1B		CL:0000753	type 1 cone bipolar cell (sensu Mus)	missing child term
106	BC2		CL:0000754	type 2 cone bipolar cell (sensu Mus)	perfect match
107	BC3A		CL:0004213	type 3a cone bipolar cell	perfect match
108	BC3B		CL:0004214	type 3b cone bipolar cell	perfect match
109	BC4		CL:0000756	type 4 cone bipolar cell (sensu Mus)	perfect match
110	BC5A		CL:0004215	type 5a cone bipolar cell	perfect match
111	BC5B		CL:0004216	type 5b cone bipolar cell	perfect match
112	BC5C		CL:0000757	type 5 cone bipolar cell (sensu Mus)	missing child term
113	BC5D		CL:0000757	type 5 cone bipolar cell (sensu Mus)	missing child term
114	BC6		CL:0000758	type 6 cone bipolar cell (sensu Mus)	perfect match
115	BC7		CL:0000759	type 7 cone bipolar cell (sensu Mus)	perfect match
116	BC8		CL:0000760	type 8 cone bipolar cell (sensu Mus)	perfect match
117	BC9		CL:0000761	type 9 cone bipolar cell (sensu Mus)	perfect match
118	Cone		CL:0000573	retinal cone cell	perfect match
119	Endothelial		CL:0000115	endothelial cell	perfect match
120	HC	horizontal cells	CL:0000745	retina horizontal cell	perfect match
121	MG	Muller glia cells	CL:0000636	Mueller cell	perfect match
122	Microglia		CL:0000129	microglial cell	perfect match
123	Pericyte		CL:0000669	pericyte	perfect match
124	RBC	rod bipolar cell	CL:0000751	rod bipolar cell	perfect match
125	RGC	retinal ganglion cells	CL:0000740	retinal ganglion cell	perfect match
126	RPE	retinal pigment epithelial cells	CL:0002586	retinal pigment epithelial cell	perfect match
127	Rod		CL:0000604	retinal rod cell	perfect match

	infoStage	notes_stage	stageId_	stageName_	stageAnnotationStatus_	infoStage_new
0	Postnatal day 14	they use the obsolete term MmusDv:0000046, updated to the new correct term; over 14 days and under 21 days old	MmusDv:0000141	2-week-old stage	missing child term	Postnatal day 14
1	Postnatal day 17	they use the obsolete term MmusDv:0000046, updated to the new correct term; over 14 days and under 21 days old	MmusDv:0000141	2-week-old stage	missing child term	Postnatal day 17
2	Postnatal day 180	they use the obsolete term MmusDv:0000098, updated to the new correct term; over 175 days and under 182 days old	MmusDv:0000171	25-week-old stage	missing child term	Postnatal day 180
3	Postnatal day 40	they use the obsolete term MmusDv:0000049, updated to the new correct term; over 35 days and under 42 days old	MmusDv:0000150	5-week-old stage	missing child term	Postnatal day 40
4	Postnatal day 90	they use the obsolete term MmusDv:0000056, updated to the new correct term; over 84 days and under 92 days old	MmusDv:0000158	12-week-old stage	missing child term	Postnatal day 90
5	Postnatal month 4	they use 4 month-old stage, however we know this is postnatal day 120, so 17 weeks is more accurate; over 119 days and under 126 days old	MmusDv:0000163	17-week-old stage	missing child term	Postnatal day 120
6	Postnatal week 8	they use the obsolete term MmusDv:0000052, updated to the new correct term; over 56 days and under 63 days old	MmusDv:0000154	8-week-old stage	missing child term	Postnatal day 56

	accession
Bipolar1_ATCGTCAGCACC	GSE81904
aRGC1_AAACGGGGTTACGCGC-1	GSE133382
MouseACS2_GAACCTATCTGTCCGT-1	GSE149715
CTRLC57AllOther1_AACCATGGTAGTACCT-1	GSE199317
CtCreRGCS1_AAAGCAACAGAAGCAC-1	GSE201254
10x3_Ms_WT_P14_AAACCCAAGGGATCTG-1	GSE243413
rgc_T2-AGGGCTCTCCGAGCTG-1	NaN

	sampleid
10x3_Ms_WT_P14_AAACCCAAGGGATCTG-1	10x3_Ms_WT_P14
10x3_Ms_WT_P40_AAAGGTAGTCGGCACT-1	10x3_Ms_WT_P40
10x3_Ms_WT_P90_ACACTGACAGCACCCA-1	10x3_Ms_WT_P90
10x3_Ms_WT_P180_1_ACCAACACACGCTTAA-1	10x3_Ms_WT_P180
10x3_Ms_WT_PBS_2L_AAACGAAAGTCACGAG-1	10x3_Ms_WT_PBS_2L
10x_Retina0313v2_AAACCTGTCAAACAAG-1	10x_Retina0313v2
10x_Retina0423Cd73N_AAACCCAAGATGGGCT-1	10x_Retina0423Cd73N
10x_Retina0426Cd73N_AAACCCACACGGCCAT-1	10x_Retina0426Cd73N
10x_mouse_CD90_ATACCGACATGCCGCA-1	10x_mouse_CD90
10x_retina0315CD73NDRv2_AAACGGGGTCTAGTGT-1	10x_retina0315CD73NDRv2
10x_retina0315CD73Nv2_AAACCTGAGGCGACAT-1	10x_retina0315CD73Nv2
10x_retina0315CD73Nv3_AAACGAATCTGATTCT-1	10x_retina0315CD73Nv3
10x_retina0401CD73Nv3_AAACCCAAGCGAAACC-1	10x_retina0401CD73Nv3
10x_retina_WT_4M_1_GGTTAACAGGTTACCT-1	10x_retina_WT_4M
Retina_3_AACCGCGAGAATTCCC-1	RGC_3_AC
Retina_1_AAAGTAGGTCGCATCG-1	RGC_live_AC

	author_cell_type	majorclass	cell_type
10x3_Ms_WT_P14_GTTATGGTCACTTCTA-1	1_W3D1.1	RGC	retinal ganglion cell
10x3_Ms_WT_P14_GACCCAGCAGGCGATA-1	2_W3D1.2	RGC	retinal ganglion cell
10x3_Ms_WT_P180_1_ATCTCTAGTGGAACAC-1	3_FminiON	RGC	retinal ganglion cell
10x3_Ms_WT_P14_TTTGATCAGGCGTCCT-1	4_FminiOFF	RGC	retinal ganglion cell
10x3_Ms_WT_P14_TAGGTTGAGAGCCATG-1	5_J-RGC	RGC	retinal ganglion cell
10x3_Ms_WT_P14_CCTCACAGTTCTCCCA-1	6_W3B	RGC	retinal ganglion cell
10x3_Ms_WT_P14_AGACAAAAGCATCAGG-1	7_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P180_1_CAGCACGAGTGCCGAA-1	8_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P180_2_CGACAGCTCGACCACG-1	9_Tbr1_Novel	RGC	retinal ganglion cell
10x_retina0315CD73NDRv2_CATGGCGGTGTCGCTG-1	10_Novel	RGC	retinal ganglion cell
10x_retina0315CD73NDRv2_1_AGATTGCCATCGGTTA-1	11_Novel	RGC	retinal ganglion cell
10x_retina0315CD73Nv2_CATGCCTAGTCATGCT-1	12_ooDS_NT	RGC	retinal ganglion cell
10x_retina0401CD73Nv3_GCTACAATCTGGTGGC-1	13_Novel	RGC	retinal ganglion cell
10x_retina0315CD73Nv2_CATCGGGGTTACGGAG-1	14_ooDS_Cck	RGC	retinal ganglion cell
10x_retina0315CD73Nv2_CATGCCTCAGACAAAT-1	15_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P14_TCCGAAAAGGTTCAGG-1	16_ooDS_DV	RGC	retinal ganglion cell
10x3_Ms_WT_P180_1_AGGAAATCACGACGTC-1	17_Tbr1_S1	RGC	retinal ganglion cell
10x3_Ms_WT_P180_1_GGATCTACATGGCACC-1	18_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P180_1_CTACTATGTGGCTTGC-1	19_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P180_1_CTAACCCAGCGTGTCC-1	20_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P90_TTGTGTTCAGTACTAC-1	21_Tbr1_S2	RGC	retinal ganglion cell
10x3_Ms_WT_P14_CGGCAGTGTGGCTAGA-1	22_M5	RGC	retinal ganglion cell
Retina_3_CTAACTTAGAGTTGGC-1	23_W3D2	RGC	retinal ganglion cell
10x3_Ms_WT_P14_ATTCCTACAAACGTGG-1	24_Novel	RGC	retinal ganglion cell
10x_retina0315CD73NDRv2_1_TGCACCTTCTACGAGT-1	25_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P180_2_AGCGCTGGTATAGGGC-1	26_Novel	RGC	retinal ganglion cell
Retina_3_ACGCCGAGTCGAACAG-1	27_Novel	RGC	retinal ganglion cell
Retina_3_ACGCAGCCATCTATGG-1	28_FmidiOFF	RGC	retinal ganglion cell
10x_retina0315CD73NDRv2_AACACGTAGGCAATTA-1	29_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P180_2_ACCCTTGAGTATGACA-1	30_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P90_CACGAATCACACCAGC-1	31_M2	RGC	retinal ganglion cell
Retina_3_ACGAGCCGTGACAAAT-1	32_F_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P180_2_CACGAATAGGGTTGCA-1	33_M1	RGC	retinal ganglion cell
Retina_1_TACTTGTTCAAGAAGT-1	34_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P40_GGCGTCACAGCAGTCC-1	35_Novel	RGC	retinal ganglion cell
Retina_3_CGTGTAATCCTCAATT-1	36_Novel	RGC	retinal ganglion cell
10x_retina0315CD73Nv2_CTTAACTGTGTGCCTG-1	37_Novel	RGC	retinal ganglion cell
10x_retina0315CD73Nv2_TACGGGCTCTCGGACG-1	38_FmidiON	RGC	retinal ganglion cell
10x3_Ms_WT_P40_GAAGGACGTCATAGTC-1	40_M1dup	RGC	retinal ganglion cell
10x_retina0315CD73NDRv2_1_TATTACCAGTTAAGTG-1	41_AlphaONT	RGC	retinal ganglion cell
10x3_Ms_WT_P180_1_TACCTGCCAATACGCT-1	43_AlphaONS	RGC	retinal ganglion cell
10x3_Ms_WT_P14_GGGAGTACATTGGATC-1	44_Novel	RGC	retinal ganglion cell
10x3_Ms_WT_P14_CTTCGGTGTTATCTTC-1	AC	AC	amacrine cell
10x3_Ms_WT_P14_ATCATTCTCCTCAGAA-1	AC_1	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_ACCTACCGTCGACGCT-1	AC_2	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_AACCAACCAGCTCATA-1	AC_3	AC	glycinergic amacrine cell
10x3_Ms_WT_P14_AGATCCATCAAAGAAC-1	AC_4	AC	glycinergic amacrine cell
10x3_Ms_WT_P14_ATACCTTGTGCACAAG-1	AC_5	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_TATGTTCAGAGGCGTT-1	AC_6	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_GGGCTCAAGAGCACTG-1	AC_7	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CAACCAATCATTGCCC-1	AC_8	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_AATCACGCACCGTGCA-1	AC_9	AC	glycinergic amacrine cell
10x3_Ms_WT_P14_CAAGGGACAAATGAGT-1	AC_10	AC	amacrine cell
10x3_Ms_WT_P14_ACTTTGTAGGTAGATT-1	AC_11	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_AACACACAGATCACTC-1	AC_12	AC	glycinergic amacrine cell
10x3_Ms_WT_P14_ACATCCCCACAAAGCG-1	AC_13	AC	glycinergic amacrine cell
10x3_Ms_WT_P180_2_AAAGGTAGTTCGGCTG-1	AC_14	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CTACGGGTCCCGAGAC-1	AC_15	AC	glycinergic amacrine cell
Retina_3_TAGTTGGGTCTCATCC-1	AC_16	AC	amacrine cell
10x3_Ms_WT_P14_AAAGTGAAGCATGCGA-1	AC_17	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_GTCGTAAGTGCGGTAA-1	AC_18	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_ACACGCGTCACAGAGG-1	AC_19	AC	glycinergic amacrine cell
10x3_Ms_WT_P14_CGTAATGCAGAACTCT-1	AC_20	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CGGGTGTAGGAAACGA-1	AC_21	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_GCCTGTTTCGACCACG-1	AC_22	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CAATCGAAGCGTTAGG-1	AC_23	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_TAGACTGGTGAGGCAT-1	AC_24	AC	amacrine cell
10x3_Ms_WT_P14_AAGTCGTAGCCATATC-1	AC_25	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_ATGAAAGCATGGCGCT-1	AC_26	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CCCTTAGGTTGGTGTT-1	AC_27	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_AGGTCTACACGCGCTA-1	AC_28	AC	glycinergic amacrine cell
10x3_Ms_WT_P14_TCACTATTCATACGGT-1	AC_29	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_ATTACCTAGTGTACAA-1	AC_30	AC	amacrine cell
10x3_Ms_WT_P180_1_GGACGTCTCCGTACGG-1	AC_31	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_CTTCTCTGTGCCCGTA-1	AC_32	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_AGGGTGATCGCATAGT-1	AC_33	AC	glycinergic amacrine cell
10x3_Ms_WT_P40_AAACGAACACCGCTGA-1	AC_34	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_ACAACCACACACTGGC-1	AC_35	AC	glycinergic amacrine cell
10x3_Ms_WT_P14_ATATCCTTCGCAGTCG-1	AC_36	AC	amacrine cell
10x3_Ms_WT_P180_1_TGCTCCACACTGGATT-1	AC_37	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CAGGCCACAAGATGGC-1	AC_38	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_ATTCACTAGATTTGCC-1	AC_39	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_GTGGGAAGTGGTAACG-1	AC_40	AC	GABAergic amacrine cell
Retina_3_AAAGATGCAATGGTCT-1	AC_41	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CCCTTAGAGGATCATA-1	AC_42	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_GGCGTCATCGGAAGGT-1	AC_43	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_GAAATGACAGAATTCC-1	AC_44	AC	GABAergic amacrine cell
Retina_3_ACCCACTTCCACGACG-1	AC_45	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_AGGACGATCTAGGAAA-1	AC_46	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_ATACTTCTCGGTAACT-1	AC_47	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_ATTTCACAGTACAGCG-1	AC_48	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_GGTCTGGCATGGGTTT-1	AC_50	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_CATCAAGGTATGATCC-1	AC_51	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CAACGGCCATCCCGTT-1	AC_52	AC	GABAergic amacrine cell
Retina_3_ACGCCAGTCTCATTCA-1	AC_54	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_2_ATCCCTGTCTCGGGAC-1	AC_55	AC	GABAergic amacrine cell
10x3_Ms_WT_P90_ATCGTCCCACACCTTC-1	AC_56	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_ATGGGAGTCTATACTC-1	AC_57	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_AGGGTGAAGGTTCATC-1	AC_58	AC	GABAergic amacrine cell
10x_retina0401CD73Nv3_CAATCGAAGATCACTC-1	AC_59	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_1_CAGGCCAGTGGACCTC-1	AC_60	AC	GABAergic amacrine cell
Retina_3_AAGGTTCCACTAGTAC-1	AC_61	AC	GABAergic amacrine cell
10x3_Ms_WT_P180_2_GTTCATTAGAGCAGCT-1	AC_63	AC	GABAergic amacrine cell
10x3_Ms_WT_P14_CATACCCTCATGAGTC-1	BC	BC	retinal bipolar neuron
10x3_Ms_WT_P14_ATACCTTTCCGCATAA-1	BC1A	BC	type 1 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AGATCCAAGATGTAGT-1	BC1B	BC	type 1 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AGGTCATTCTTACTGT-1	BC2	BC	type 2 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AACACACCACGCAAAG-1	BC3A	BC	type 3a cone bipolar cell
10x3_Ms_WT_P14_AAAGAACGTTAAACAG-1	BC3B	BC	type 3b cone bipolar cell
10x3_Ms_WT_P14_AGAGCCCAGTTGCGAG-1	BC4	BC	type 4 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AAACGAACAATGTTGC-1	BC5A	BC	type 5a cone bipolar cell
10x3_Ms_WT_P14_AAAGTCCCAGGGCTTC-1	BC5B	BC	type 5b cone bipolar cell
10x3_Ms_WT_P14_AACAAAGAGATGACCG-1	BC5C	BC	type 5 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AAAGGTAAGTGTACCT-1	BC5D	BC	type 5 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AAACGAAAGACTCTAC-1	BC6	BC	type 6 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_ACTACGAAGACATATG-1	BC7	BC	type 7 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AACAGGGTCATGCCCT-1	BC8	BC	type 8 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AAATGGAGTCACTTAG-1	BC9	BC	type 9 cone bipolar cell (sensu Mus)
10x3_Ms_WT_P14_AACAAGACAGCCATTA-1	Cone	Cone	retinal cone cell
10x3_Ms_WT_P14_AACAACCCAAGCTGTT-1	Endothelial	Endothelial	endothelial cell
10x3_Ms_WT_P14_AAACGAATCCTACAAG-1	HC	HC	retina horizontal cell
10x3_Ms_WT_P14_AAACCCATCGGCCCAA-1	MG	MG	Mueller cell
10x3_Ms_WT_P14_AAACGAACAGTGGTGA-1	Microglia	Microglia	microglial cell
10x3_Ms_WT_P14_AGTAGTCAGGTGATCG-1	Pericyte	Pericyte	pericyte
10x3_Ms_WT_P14_AAACCCAAGGGATCTG-1	RBC	BC	rod bipolar cell
10x3_Ms_WT_P14_AACCCAAGTGTACATC-1	RGC	RGC	retinal ganglion cell
10x3_Ms_WT_P14_AACCACAGTGAGACCA-1	RPE	RPE	retinal pigment epithelial cell
10x3_Ms_WT_P14_AAACCCAGTAGCTAAA-1	Rod	Rod	retinal rod cell

SRP461573 / GSE243413¶

annotation summary¶

set variables, import packages, define functions¶

10X - barcodes and annotations¶

check samples/libraries¶

check author annotations - all cells¶

check author annotations - subset files¶

amacrine subset cell annotations¶

bipolar subset cell annotations¶

RGC subset cell annotations¶

sampleid to library_id comparison¶

create barcode file of interest¶

script¶

library annnotations¶

anatomical entity¶

stage¶

sex, strain, genotype, speciesId¶

protocol & RNAseqTags¶

condition & comments¶

annotator id, last modification date¶

comments¶

save complete file with correct columns¶

script - barcode (10X only)¶

check library names match¶

cell type annotation - 10X version¶

looking into differences between h5ad CL annotations and my annotations¶

experiment annotations¶

experiment and protocol details¶

paper and xrefs¶

comments¶

save complete file¶

QA time¶

to add things here¶

check columns match¶

view files¶

add annotations to git¶

add annotation folder and script to git¶

	sampleid
10x3_Ms_WT_P14_AAAGTGAAGCATGCGA-1	10x3_Ms_WT_P14
10x3_Ms_WT_P40_TCCGATCGTCTACGAT-1	10x3_Ms_WT_P40
10x3_Ms_WT_P90_AGGCATTGTCTTCTAT-1	10x3_Ms_WT_P90
10x3_Ms_WT_P180_1_ACCCAAAGTCTCCTGT-1	10x3_Ms_WT_P180
10x3_Ms_WT_PBS_2L_AGATCGTAGGCAGGGA-1	10x3_Ms_WT_PBS_2L
10x_Retina0313v2_GGGCACTGTGGGTATG-1	10x_Retina0313v2
10x_mouse_CD90_TCTCACGTCTGCGTCT-1	10x_mouse_CD90
10x_retina0315CD73NDRv2_4_CGTTCTGCAAGGTTTC-1	10x_retina0315CD73NDRv2
10x_retina0315CD73Nv2_TAGACCACAGTCTTCC-1	10x_retina0315CD73Nv2
10x_retina0315CD73Nv3_CGCGTGAAGTCGTCTA-1	10x_retina0315CD73Nv3
10x_retina0401CD73Nv3_TGACAGTCAATCACGT-1	10x_retina0401CD73Nv3
10x_retina_WT_4M_1_TGTTTGTTCTCGACGG-1	10x_retina_WT_4M
Retina_3_TCTATTGTCGATAGAA-1	RGC_3_AC
Retina_1_AAAGTAGAGTGAATTG-1	RGC_live_AC

	sampleid
10x3_Ms_WT_P14_AAACCCAAGGGATCTG-1	10x3_Ms_WT_P14
10x3_Ms_WT_P40_AAACGAAAGCCGTTAT-1	10x3_Ms_WT_P40
10x3_Ms_WT_P90_AAACGAAAGTAGCAAT-1	10x3_Ms_WT_P90
10x3_Ms_WT_P180_1_AAACCCAGTGGTTTGT-1	10x3_Ms_WT_P180
10x3_Ms_WT_PBS_2L_AAACGAAAGTCACGAG-1	10x3_Ms_WT_PBS_2L
10x_Retina0313v2_AAACCTGTCAAACAAG-1	10x_Retina0313v2
10x_Retina0423Cd73N_AAACCCAAGAACAGGA-1	10x_Retina0423Cd73N
10x_Retina0426Cd73N_AAACCCAAGCGATGGT-1	10x_Retina0426Cd73N
10x_retina0315CD73NDRv2_AAACCTGAGGATGGAA-1	10x_retina0315CD73NDRv2
10x_retina0315CD73Nv2_AAACCTGAGGAGCGAG-1	10x_retina0315CD73Nv2
10x_retina0315CD73Nv3_AAACCCAAGCGTGCCT-1	10x_retina0315CD73Nv3
10x_retina0401CD73Nv3_AAACCCAAGAGAGAAC-1	10x_retina0401CD73Nv3
10x_retina_WT_4M_1_AAAGTCCAGCTAGAAT-1	10x_retina_WT_4M
Retina_3_AACCGCGAGAATTCCC-1	RGC_3_AC
Retina_1_AAAGTAGGTCGCATCG-1	RGC_live_AC

	sampleid
10x3_Ms_WT_P14_AGACAAAAGCATCAGG-1	10x3_Ms_WT_P14
10x3_Ms_WT_P40_CTCTCGAAGATCCCGC-1	10x3_Ms_WT_P40
10x3_Ms_WT_P90_TGGAGAGCATCCGAAT-1	10x3_Ms_WT_P90
10x3_Ms_WT_P180_1_TTTCATGAGCTTCTAG-1	10x3_Ms_WT_P180
10x_mouse_CD90_CTCCTTTTCCCAGTGG-1	10x_mouse_CD90
10x_retina0315CD73NDRv2_AGGCCGTCAGGAACGT-1	10x_retina0315CD73NDRv2
10x_retina0315CD73Nv2_CTCGGGATCCCTCAGT-1	10x_retina0315CD73Nv2
10x_retina0315CD73Nv3_CTACTATTCGTTCTAT-1	10x_retina0315CD73Nv3
10x_retina0401CD73Nv3_AGGCCACAGCGTTAGG-1	10x_retina0401CD73Nv3
Retina_3_AACCGCGCATCAGTAC-1	RGC_3_AC
Retina_1_CGGTTAAAGTAGGTGC-1	RGC_live_AC

	sampleid	library_platform
10x_Retina0313v2_AAACCTGTCAAACAAG-1	10x_Retina0313v2	10x-3'-v2
10x_retina0315CD73NDRv2_AAACGGGGTCTAGTGT-1	10x_retina0315CD73NDRv2	10x-3'-v2
10x_retina0315CD73Nv2_AAACCTGAGGCGACAT-1	10x_retina0315CD73Nv2	10x-3'-v2
Retina_3_AACCGCGAGAATTCCC-1	RGC_3_AC	10x-3'-v2
Retina_1_AAAGTAGGTCGCATCG-1	RGC_live_AC	10x-3'-v2
10x3_Ms_WT_P14_AAACCCAAGGGATCTG-1	10x3_Ms_WT_P14	10x-3'-v3
10x3_Ms_WT_P180_1_ACCAACACACGCTTAA-1	10x3_Ms_WT_P180	10x-3'-v3
10x3_Ms_WT_P40_AAAGGTAGTCGGCACT-1	10x3_Ms_WT_P40	10x-3'-v3
10x3_Ms_WT_P90_ACACTGACAGCACCCA-1	10x3_Ms_WT_P90	10x-3'-v3
10x3_Ms_WT_PBS_2L_AAACGAAAGTCACGAG-1	10x3_Ms_WT_PBS_2L	10x-3'-v3
10x_Retina0423Cd73N_AAACCCAAGATGGGCT-1	10x_Retina0423Cd73N	10x-3'-v3
10x_Retina0426Cd73N_AAACCCACACGGCCAT-1	10x_Retina0426Cd73N	10x-3'-v3
10x_retina0315CD73Nv3_AAACGAATCTGATTCT-1	10x_retina0315CD73Nv3	10x-3'-v3
10x_retina0401CD73Nv3_AAACCCAAGCGAAACC-1	10x_retina0401CD73Nv3	10x-3'-v3
10x_retina_WT_4M_1_GGTTAACAGGTTACCT-1	10x_retina_WT_4M	10x-3'-v3
10x_mouse_CD90_ATACCGACATGCCGCA-1	10x_mouse_CD90	10x-3'-v3

	barcodes	nCount_RNA	nFeature_RNA	percent.mt	pANN	sampleid	subclass_label	majorclass	author_cell_type	age	...	cell_type	assay	disease	organism	sex	tissue	self_reported_ethnicity	development_stage	observation_joinid	sample_full
81014	10x_retina0315CD73NDRv2_AAACGGGGTCTAGTGT-1	964.0	620.0	9.232365	0.000000	10x_retina0315CD73NDRv2	NaN	BC	RBC	P56	...	rod bipolar cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	WRt(V=w%O7	10x_retina0315CD73NDRv2
81015	10x_retina0315CD73NDRv2_AAACGGGTCAAGCCTA-1	1072.0	634.0	9.514925	0.000000	10x_retina0315CD73NDRv2	NaN	BC	RBC	P56	...	rod bipolar cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	UEGmVk\|@^<	10x_retina0315CD73NDRv2
81016	10x_retina0315CD73NDRv2_AAAGATGTCTTTACGT-1	812.0	533.0	8.866995	0.000000	10x_retina0315CD73NDRv2	NaN	BC	RBC	P56	...	rod bipolar cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	f%U=W;QE_;	10x_retina0315CD73NDRv2
81017	10x_retina0315CD73NDRv2_AAAGCAACACCCAGTG-1	1270.0	703.0	3.464567	0.000000	10x_retina0315CD73NDRv2	NaN	BC	RBC	P56	...	rod bipolar cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	BOJNOGZyea	10x_retina0315CD73NDRv2
81018	10x_retina0315CD73NDRv2_AAAGCAACATGTAGTC-1	1036.0	630.0	6.853282	0.095238	10x_retina0315CD73NDRv2	NaN	BC	RBC	P56	...	rod bipolar cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	7>X_{1@5<6	10x_retina0315CD73NDRv2
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
112058	10x_retina0315CD73NDRv2_GGACAGAGTCGCGGTT-1	553.0	376.0	8.137432	0.238095	10x_retina0315CD73NDRv2	NaN	RGC	3_FminiON	P56	...	retinal ganglion cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	M$$C+K1<mk	10x_retina0315CD73NDRv2
112064	10x_retina0315CD73NDRv2_AACACGTAGGCAATTA-1	4092.0	1333.0	0.122190	0.190476	10x_retina0315CD73NDRv2	NaN	RGC	29_Novel	P56	...	retinal ganglion cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	#wpn+mRbSl	10x_retina0315CD73NDRv2
112065	10x_retina0315CD73NDRv2_CACAGTAAGCCACGTC-1	6216.0	1534.0	0.144788	0.190476	10x_retina0315CD73NDRv2	NaN	RGC	29_Novel	P56	...	retinal ganglion cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	AIAydXNO@C	10x_retina0315CD73NDRv2
112066	10x_retina0315CD73NDRv2_CTAAGACTCCGTAGTA-1	6815.0	1569.0	0.132062	0.190476	10x_retina0315CD73NDRv2	NaN	RGC	29_Novel	P56	...	retinal ganglion cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	Apt0)&4avK	10x_retina0315CD73NDRv2
112067	10x_retina0315CD73NDRv2_CATGGCGGTGTCGCTG-1	5696.0	1576.0	1.018258	0.190476	10x_retina0315CD73NDRv2	NaN	RGC	10_Novel	P56	...	retinal ganglion cell	10x 3' v2	normal	Mus musculus	male	retina	na	8 weeks	q@<AS+W*no	10x_retina0315CD73NDRv2

	sampleid	sample_full
0	10x3_Ms_WT_P14	10x3_Ms_WT_P14
5829	10x3_Ms_WT_P180	10x3_Ms_WT_P180 reaction 1
5858	10x3_Ms_WT_P180	10x3_Ms_WT_P180 reaction 2
21679	10x3_Ms_WT_P40	10x3_Ms_WT_P40
28264	10x3_Ms_WT_P90	10x3_Ms_WT_P90
32604	10x3_Ms_WT_PBS_2L	10x3_Ms_WT_PBS_2L
37700	10x_Retina0313v2	10x_Retina0313v2
38867	10x_Retina0423Cd73N	10x_Retina0423Cd73N
59975	10x_Retina0426Cd73N	10x_Retina0426Cd73N
177070	10x_mouse_CD90	10x_mouse_CD90
81014	10x_retina0315CD73NDRv2	10x_retina0315CD73NDRv2 reaction 1
81415	10x_retina0315CD73NDRv2	10x_retina0315CD73NDRv2 reaction 2
83439	10x_retina0315CD73NDRv2	10x_retina0315CD73NDRv2 reaction 3
85695	10x_retina0315CD73NDRv2	10x_retina0315CD73NDRv2 reaction 4
88012	10x_retina0315CD73NDRv2	10x_retina0315CD73NDRv2 reaction 5
112073	10x_retina0315CD73Nv2	10x_retina0315CD73Nv2
133053	10x_retina0315CD73Nv3	10x_retina0315CD73Nv3
137012	10x_retina0401CD73Nv3	10x_retina0401CD73Nv3
173396	10x_retina_WT_4M	10x_retina_WT_4M reaction 1
173397	10x_retina_WT_4M	10x_retina_WT_4M reaction 2
177090	RGC_3_AC	RGC_3_AC
184652	RGC_live_AC	RGC_live_AC

	#libraryId	experimentId	platform	SRSId	anatId	anatName	url_GSM	infoOrgan	infoStage	anatAnnotationStatus	sex	genotype	speciesId	protocol	protocolType	lib_name	sampleName	condition	lastModificationDate
0	SRX21819804	SRP461573	Illumina NovaSeq 6000	SRS18920590	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785371	retina	Postnatal month 4	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	RGC_live_AC	SAMN37446807	CD90.2 enrichment	2024-12-11
1	SRX21819803	SRP461573	Illumina NovaSeq 6000	SRS18920589	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785370	retina	Postnatal month 4	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	RGC_3_AC	SAMN37446808	CD90.2 enrichment	2024-12-11
2	SRX21819802	SRP461573	Illumina NovaSeq 6000	SRS18920588	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785369	retina	Postnatal month 4	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina_WT_4M reaction 2	SAMN37446809	No enrichment	2024-12-11
3	SRX21819801	SRP461573	Illumina NovaSeq 6000	SRS18920591	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785368	retina	Postnatal month 4	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina_WT_4M reaction 1	SAMN37446810	No enrichment	2024-12-11
4	SRX21819800	SRP461573	Illumina NovaSeq 6000	SRS18920587	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785367	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0401CD73Nv3	SAMN37446811	CD73 enrichment	2024-12-11
5	SRX21819799	SRP461573	Illumina NovaSeq 6000	SRS18920586	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785366	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73Nv3	SAMN37446812	CD73 enrichment	2024-12-11
6	SRX21819798	SRP461573	Illumina NovaSeq 6000	SRS18920585	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785365	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73Nv2	SAMN37446813	CD73 enrichment	2024-12-11
7	SRX21819797	SRP461573	Illumina NovaSeq 6000	SRS18920584	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785364	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 5	SAMN37446814	CD73 enrichment	2024-12-11
8	SRX21819796	SRP461573	Illumina NovaSeq 6000	SRS18920582	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785363	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 4	SAMN37446815	CD73 enrichment	2024-12-11
9	SRX21819795	SRP461573	Illumina NovaSeq 6000	SRS18920583	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785362	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 3	SAMN37446816	CD73 enrichment	2024-12-11
10	SRX21819794	SRP461573	Illumina NovaSeq 6000	SRS18920581	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785361	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 2	SAMN37446817	CD73 enrichment	2024-12-11
11	SRX21819793	SRP461573	Illumina NovaSeq 6000	SRS18920580	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785360	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 1	SAMN37446818	CD73 enrichment	2024-12-11
12	SRX21819792	SRP461573	Illumina NovaSeq 6000	SRS18920579	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785359	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_mouse_CD90	SAMN37446819	CD90.2 enrichment	2024-12-11
13	SRX21819791	SRP461573	Illumina NovaSeq 6000	SRS18920578	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785358	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_Retina0426Cd73N	SAMN37446820	CD73 enrichment	2024-12-11
14	SRX21819790	SRP461573	Illumina NovaSeq 6000	SRS18920576	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785357	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_Retina0423Cd73N	SAMN37446821	CD73 enrichment	2024-12-11
15	SRX21819789	SRP461573	Illumina NovaSeq 6000	SRS18920575	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785356	retina	Postnatal week 8	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_Retina0313v2	SAMN37446822	No enrichment	2024-12-11
16	SRX21819788	SRP461573	Illumina NovaSeq 6000	SRS18920574	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785355	retina	Postnatal day 17	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_PBS_2L	SAMN37446823	No enrichment	2024-12-11
17	SRX21819787	SRP461573	Illumina NovaSeq 6000	SRS18920577	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785354	retina	Postnatal day 90	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P90	SAMN37446824	No enrichment	2024-12-11
18	SRX21819786	SRP461573	Illumina NovaSeq 6000	SRS18920572	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785353	retina	Postnatal day 40	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P40	SAMN37446825	No enrichment	2024-12-11
19	SRX21819785	SRP461573	Illumina NovaSeq 6000	SRS18920573	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785352	retina	Postnatal day 180	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P180 reaction 2	SAMN37446826	No enrichment	2024-12-11
20	SRX21819784	SRP461573	Illumina NovaSeq 6000	SRS18920570	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785351	retina	Postnatal day 180	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P180 reaction 1	SAMN37446827	No enrichment	2024-12-11
21	SRX21819783	SRP461573	Illumina NovaSeq 6000	SRS18920571	UBERON:0000966	retina	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785350	retina	Postnatal day 14	perfect match	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P14	SAMN37446828	No enrichment	2024-12-11

	sampleid	age	development_stage	development_stage_ontology_term_id
173396	10x_retina_WT_4M	P120	4 month-old stage	MmusDv:0000064
177090	RGC_3_AC	P120	4 month-old stage	MmusDv:0000064
184652	RGC_live_AC	P120	4 month-old stage	MmusDv:0000064
0	10x3_Ms_WT_P14	P14	2 weeks	MmusDv:0000046
32604	10x3_Ms_WT_PBS_2L	P17	2 weeks	MmusDv:0000046
5829	10x3_Ms_WT_P180	P180	25 weeks	MmusDv:0000098
21679	10x3_Ms_WT_P40	P40	5 weeks	MmusDv:0000049
37700	10x_Retina0313v2	P56	8 weeks	MmusDv:0000052
38867	10x_Retina0423Cd73N	P56	8 weeks	MmusDv:0000052
59975	10x_Retina0426Cd73N	P56	8 weeks	MmusDv:0000052
81014	10x_retina0315CD73NDRv2	P56	8 weeks	MmusDv:0000052
112073	10x_retina0315CD73Nv2	P56	8 weeks	MmusDv:0000052
133053	10x_retina0315CD73Nv3	P56	8 weeks	MmusDv:0000052
137012	10x_retina0401CD73Nv3	P56	8 weeks	MmusDv:0000052
177070	10x_mouse_CD90	P56	8 weeks	MmusDv:0000052
28264	10x3_Ms_WT_P90	P90	12 weeks	MmusDv:0000056

	protocol	lib_name
0	10X Genomics V2	RGC_live_AC
15	10X Genomics V2	10x_Retina0313v2
11	10X Genomics V2	10x_retina0315CD73NDRv2 reaction 1
9	10X Genomics V2	10x_retina0315CD73NDRv2 reaction 3
8	10X Genomics V2	10x_retina0315CD73NDRv2 reaction 4
7	10X Genomics V2	10x_retina0315CD73NDRv2 reaction 5
10	10X Genomics V2	10x_retina0315CD73NDRv2 reaction 2
1	10X Genomics V2	RGC_3_AC
6	10X Genomics V2	10x_retina0315CD73Nv2
5	10X Genomics V3	10x_retina0315CD73Nv3
4	10X Genomics V3	10x_retina0401CD73Nv3
3	10X Genomics V3	10x_retina_WT_4M reaction 1
20	10X Genomics V3	10x3_Ms_WT_P180 reaction 1
2	10X Genomics V3	10x_retina_WT_4M reaction 2
12	10X Genomics V3	10x_mouse_CD90
13	10X Genomics V3	10x_Retina0426Cd73N
14	10X Genomics V3	10x_Retina0423Cd73N
16	10X Genomics V3	10x3_Ms_WT_PBS_2L
17	10X Genomics V3	10x3_Ms_WT_P90
18	10X Genomics V3	10x3_Ms_WT_P40
19	10X Genomics V3	10x3_Ms_WT_P180 reaction 2
21	10X Genomics V3	10x3_Ms_WT_P14

	author_cell_type	majorclass	cell_type	cell_type_ontology_term_id
5813	AC	AC	amacrine cell	CL:0000561
5778	AC_1	AC	GABAergic amacrine cell	CL:4030027
5797	AC_10	AC	amacrine cell	CL:0000561
5703	AC_11	AC	GABAergic amacrine cell	CL:4030027
5418	AC_12	AC	glycinergic amacrine cell	CL:4030028
5643	AC_13	AC	glycinergic amacrine cell	CL:4030028
21666	AC_14	AC	GABAergic amacrine cell	CL:4030027
5812	AC_15	AC	glycinergic amacrine cell	CL:4030028
184504	AC_16	AC	amacrine cell	CL:0000561
5235	AC_17	AC	GABAergic amacrine cell	CL:4030027
21655	AC_18	AC	GABAergic amacrine cell	CL:4030027
5631	AC_19	AC	glycinergic amacrine cell	CL:4030028
5652	AC_2	AC	GABAergic amacrine cell	CL:4030027
5810	AC_20	AC	GABAergic amacrine cell	CL:4030027
5808	AC_21	AC	GABAergic amacrine cell	CL:4030027
5817	AC_22	AC	GABAergic amacrine cell	CL:4030027
5798	AC_23	AC	GABAergic amacrine cell	CL:4030027
5823	AC_24	AC	amacrine cell	CL:0000561
5606	AC_25	AC	GABAergic amacrine cell	CL:4030027
21619	AC_26	AC	GABAergic amacrine cell	CL:4030027
5804	AC_27	AC	GABAergic amacrine cell	CL:4030027
5748	AC_28	AC	glycinergic amacrine cell	CL:4030028
5826	AC_29	AC	GABAergic amacrine cell	CL:4030027
5496	AC_3	AC	glycinergic amacrine cell	CL:4030028
5781	AC_30	AC	amacrine cell	CL:0000561
21645	AC_31	AC	GABAergic amacrine cell	CL:4030027
21638	AC_32	AC	GABAergic amacrine cell	CL:4030027
21610	AC_33	AC	glycinergic amacrine cell	CL:4030028
28261	AC_34	AC	GABAergic amacrine cell	CL:4030027
5629	AC_35	AC	glycinergic amacrine cell	CL:4030028
5775	AC_36	AC	amacrine cell	CL:0000561
21664	AC_37	AC	GABAergic amacrine cell	CL:4030027
5799	AC_38	AC	GABAergic amacrine cell	CL:4030027
5788	AC_39	AC	GABAergic amacrine cell	CL:4030027
5725	AC_4	AC	glycinergic amacrine cell	CL:4030028
21660	AC_40	AC	GABAergic amacrine cell	CL:4030027
184530	AC_41	AC	GABAergic amacrine cell	CL:4030027
5803	AC_42	AC	GABAergic amacrine cell	CL:4030027
21650	AC_43	AC	GABAergic amacrine cell	CL:4030027
21642	AC_44	AC	GABAergic amacrine cell	CL:4030027
184505	AC_45	AC	GABAergic amacrine cell	CL:4030027
5739	AC_46	AC	GABAergic amacrine cell	CL:4030027
5773	AC_47	AC	GABAergic amacrine cell	CL:4030027
5790	AC_48	AC	GABAergic amacrine cell	CL:4030027
5752	AC_5	AC	GABAergic amacrine cell	CL:4030027
21653	AC_50	AC	GABAergic amacrine cell	CL:4030027
21632	AC_51	AC	GABAergic amacrine cell	CL:4030027
5795	AC_52	AC	GABAergic amacrine cell	CL:4030027
184520	AC_54	AC	GABAergic amacrine cell	CL:4030027
21671	AC_55	AC	GABAergic amacrine cell	CL:4030027
32601	AC_56	AC	GABAergic amacrine cell	CL:4030027
5780	AC_57	AC	GABAergic amacrine cell	CL:4030027
21606	AC_58	AC	GABAergic amacrine cell	CL:4030027
173393	AC_59	AC	GABAergic amacrine cell	CL:4030027
5825	AC_6	AC	GABAergic amacrine cell	CL:4030027
21631	AC_60	AC	GABAergic amacrine cell	CL:4030027
184527	AC_61	AC	GABAergic amacrine cell	CL:4030027
21678	AC_63	AC	GABAergic amacrine cell	CL:4030027
5820	AC_7	AC	GABAergic amacrine cell	CL:4030027
5791	AC_8	AC	GABAergic amacrine cell	CL:4030027
5610	AC_9	AC	glycinergic amacrine cell	CL:4030028
5800	BC	BC	retinal bipolar neuron	CL:0000748
5767	BC1A	BC	type 1 cone bipolar cell (sensu Mus)	CL:0000753
5710	BC1B	BC	type 1 cone bipolar cell (sensu Mus)	CL:0000753
5741	BC2	BC	type 2 cone bipolar cell (sensu Mus)	CL:0000754
5420	BC3A	BC	type 3a cone bipolar cell	CL:0004213
5092	BC3B	BC	type 3b cone bipolar cell	CL:0004214
5707	BC4	BC	type 4 cone bipolar cell (sensu Mus)	CL:0000756
4999	BC5A	BC	type 5a cone bipolar cell	CL:0004215
5208	BC5B	BC	type 5b cone bipolar cell	CL:0004216
5244	BC5C	BC	type 5 cone bipolar cell (sensu Mus)	CL:0000757
5177	BC5D	BC	type 5 cone bipolar cell (sensu Mus)	CL:0000757
4935	BC6	BC	type 6 cone bipolar cell (sensu Mus)	CL:0000758
5661	BC7	BC	type 7 cone bipolar cell (sensu Mus)	CL:0000759
5490	BC8	BC	type 8 cone bipolar cell (sensu Mus)	CL:0000760
5236	BC9	BC	type 9 cone bipolar cell (sensu Mus)	CL:0000761
0	RBC	BC	rod bipolar cell	CL:0000751
5312	Cone	Cone	retinal cone cell	CL:0000573
5297	Endothelial	Endothelial	endothelial cell	CL:0000115
5083	HC	HC	retina horizontal cell	CL:0000745
4691	MG	MG	Mueller cell	CL:0000636
5065	Microglia	Microglia	microglial cell	CL:0000129
5749	Pericyte	Pericyte	pericyte	CL:0000669
112067	10_Novel	RGC	retinal ganglion cell	CL:0000740
112069	11_Novel	RGC	retinal ganglion cell	CL:0000740
133047	12_ooDS_NT	RGC	retinal ganglion cell	CL:0000740
173394	13_Novel	RGC	retinal ganglion cell	CL:0000740
133045	14_ooDS_Cck	RGC	retinal ganglion cell	CL:0000740
133050	15_Novel	RGC	retinal ganglion cell	CL:0000740
5827	16_ooDS_DV	RGC	retinal ganglion cell	CL:0000740
21604	17_Tbr1_S1	RGC	retinal ganglion cell	CL:0000740
21648	18_Novel	RGC	retinal ganglion cell	CL:0000740
21635	19_Novel	RGC	retinal ganglion cell	CL:0000740
5822	1_W3D1.1	RGC	retinal ganglion cell	CL:0000740
21634	20_Novel	RGC	retinal ganglion cell	CL:0000740
32603	21_Tbr1_S2	RGC	retinal ganglion cell	CL:0000740
5807	22_M5	RGC	retinal ganglion cell	CL:0000740
184642	23_W3D2	RGC	retinal ganglion cell	CL:0000740
5789	24_Novel	RGC	retinal ganglion cell	CL:0000740
112072	25_Novel	RGC	retinal ganglion cell	CL:0000740
21669	26_Novel	RGC	retinal ganglion cell	CL:0000740
184648	27_Novel	RGC	retinal ganglion cell	CL:0000740
184643	28_FmidiOFF	RGC	retinal ganglion cell	CL:0000740
112064	29_Novel	RGC	retinal ganglion cell	CL:0000740
5815	2_W3D1.2	RGC	retinal ganglion cell	CL:0000740
21668	30_Novel	RGC	retinal ganglion cell	CL:0000740
32602	31_M2	RGC	retinal ganglion cell	CL:0000740
184639	32_F_Novel	RGC	retinal ganglion cell	CL:0000740
21674	33_M1	RGC	retinal ganglion cell	CL:0000740
189186	34_Novel	RGC	retinal ganglion cell	CL:0000740
28263	35_Novel	RGC	retinal ganglion cell	CL:0000740
184651	36_Novel	RGC	retinal ganglion cell	CL:0000740
133051	37_Novel	RGC	retinal ganglion cell	CL:0000740
133052	38_FmidiON	RGC	retinal ganglion cell	CL:0000740
21614	3_FminiON	RGC	retinal ganglion cell	CL:0000740
28262	40_M1dup	RGC	retinal ganglion cell	CL:0000740
112071	41_AlphaONT	RGC	retinal ganglion cell	CL:0000740
21663	43_AlphaONS	RGC	retinal ganglion cell	CL:0000740
5819	44_Novel	RGC	retinal ganglion cell	CL:0000740
5828	4_FminiOFF	RGC	retinal ganglion cell	CL:0000740
5824	5_J-RGC	RGC	retinal ganglion cell	CL:0000740
5806	6_W3B	RGC	retinal ganglion cell	CL:0000740
5706	7_Novel	RGC	retinal ganglion cell	CL:0000740
21629	8_Novel	RGC	retinal ganglion cell	CL:0000740
21675	9_Tbr1_Novel	RGC	retinal ganglion cell	CL:0000740
5573	RGC	RGC	retinal ganglion cell	CL:0000740
5512	RPE	RPE	retinal pigment epithelial cell	CL:0002586
292	Rod	Rod	retinal rod cell	CL:0000604

	#libraryId	experimentId	platform	SRSId	url_GSM	infoOrgan	infoStage	sex	genotype	speciesId	protocol	protocolType	lib_name	sampleName	condition	lastModificationDate	library_contruction_protocol	source_name
0	SRX21819804	SRP461573	Illumina NovaSeq 6000	SRS18920590	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785371	retina	Postnatal month 4	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	RGC_live_AC	SAMN37446807	CD90.2 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
1	SRX21819803	SRP461573	Illumina NovaSeq 6000	SRS18920589	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785370	retina	Postnatal month 4	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	RGC_3_AC	SAMN37446808	CD90.2 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
2	SRX21819802	SRP461573	Illumina NovaSeq 6000	SRS18920588	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785369	retina	Postnatal month 4	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina_WT_4M reaction 2	SAMN37446809	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
3	SRX21819801	SRP461573	Illumina NovaSeq 6000	SRS18920591	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785368	retina	Postnatal month 4	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina_WT_4M reaction 1	SAMN37446810	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
4	SRX21819800	SRP461573	Illumina NovaSeq 6000	SRS18920587	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785367	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0401CD73Nv3	SAMN37446811	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
5	SRX21819799	SRP461573	Illumina NovaSeq 6000	SRS18920586	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785366	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73Nv3	SAMN37446812	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
6	SRX21819798	SRP461573	Illumina NovaSeq 6000	SRS18920585	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785365	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73Nv2	SAMN37446813	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
7	SRX21819797	SRP461573	Illumina NovaSeq 6000	SRS18920584	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785364	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 5	SAMN37446814	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
8	SRX21819796	SRP461573	Illumina NovaSeq 6000	SRS18920582	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785363	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 4	SAMN37446815	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
9	SRX21819795	SRP461573	Illumina NovaSeq 6000	SRS18920583	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785362	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 3	SAMN37446816	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
10	SRX21819794	SRP461573	Illumina NovaSeq 6000	SRS18920581	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785361	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 2	SAMN37446817	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
11	SRX21819793	SRP461573	Illumina NovaSeq 6000	SRS18920580	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785360	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_retina0315CD73NDRv2 reaction 1	SAMN37446818	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
12	SRX21819792	SRP461573	Illumina NovaSeq 6000	SRS18920579	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785359	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_mouse_CD90	SAMN37446819	CD90.2 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
13	SRX21819791	SRP461573	Illumina NovaSeq 6000	SRS18920578	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785358	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_Retina0426Cd73N	SAMN37446820	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
14	SRX21819790	SRP461573	Illumina NovaSeq 6000	SRS18920576	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785357	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_Retina0423Cd73N	SAMN37446821	CD73 enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
15	SRX21819789	SRP461573	Illumina NovaSeq 6000	SRS18920575	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785356	retina	Postnatal week 8	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x_Retina0313v2	SAMN37446822	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
16	SRX21819788	SRP461573	Illumina NovaSeq 6000	SRS18920574	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785355	retina	Postnatal day 17	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_PBS_2L	SAMN37446823	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
17	SRX21819787	SRP461573	Illumina NovaSeq 6000	SRS18920577	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785354	retina	Postnatal day 90	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P90	SAMN37446824	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
18	SRX21819786	SRP461573	Illumina NovaSeq 6000	SRS18920572	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785353	retina	Postnatal day 40	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P40	SAMN37446825	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
19	SRX21819785	SRP461573	Illumina NovaSeq 6000	SRS18920573	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785352	retina	Postnatal day 180	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P180 reaction 2	SAMN37446826	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
20	SRX21819784	SRP461573	Illumina NovaSeq 6000	SRS18920570	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785351	retina	Postnatal day 180	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P180 reaction 1	SAMN37446827	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina
21	SRX21819783	SRP461573	Illumina NovaSeq 6000	SRS18920571	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM7785350	retina	Postnatal day 14	M	wild-type	10090	10X Genomics V2,10X Genomics	3'end	10x3_Ms_WT_P14	SAMN37446828	No enrichment	2024-12-11	We have generated 16 scRNA-seq samples of the mouse C57BL6/J retina. After dissection, retinas were dissociated into single cells using papain-based enzyme following the published protocol 10. With activated 45U of papain (Worthington, Cat. #LS003126) solution (1mg L-Cystine, Sigma; 8 KU of DNase I, Affymetrix; in 5 ml DPBS), retina was incubated at 37C for ~20min. Which was followed by the replacement of incubation buffer with 2ml ovomucoid solution (15 mg ovomucoid, Worthington Biochemical; 15 mg BSA Thermo Fisher Scientific; in 10 ml DPBS) and 500ul deactivated FBS. The retina tissue was carefully triturated and filtered by 20 um plastic mesh. Repeat the step with additional 1ml ovomucoid solution until no tissue is visible. Spin the cells down at 300g, 4C for 10 min, and cells were used in the next step. To deplete the photoreceptors, cells were resuspended in 0.5% BSA and stained with CD73-PE antibody for 10min at 4C (for each million cells, add 98ul 0.5% BSA with 2ul CD73-PE antibody), and washed with 35 ml 0.5% BSA at 4C for 10min. After being stained with Anti-PE microbeads (for each million cells, add 80ul 0.5% BSA and 20ul microbeads), for 15 min at 4C, cells were washed and resuspended in 0.5% BSA. CD73 negative neuronal cells were enriched by autoMACS Pro Separator (Miltenyi Biotec) DEPLETES mode and ready for the next step. Similarly, CD90.2 positive neuronal cells were enriched with CD90.2 microbeads (for each 10million cells, 90ul 0.5% BSA and 10ul CD90.2 microbeads were used) and autoMACS POSSEL-S mode. Cells viability was 85%-87% when checked with DAPI staining under microscope. Guided by 10X manufacturer's protocols (https://www.10xgenomics.com), single cell cDNA library was prepared and sequenced. Briefly, single cell suspension was loaded on a Chromium controller to obtain single cell GEMS (Gel Beads-In-Emulsions) for the reaction. The library was prepared with Chromium Next GEM single cell 3' kit V2 (10X Genomics) and sequenced on Illumina Novaseq 6000 (https://www.illumina.com). Our in-house generated single cell data was sequenced at the Single Cell Genomics Core at Baylor College of Medicine.	retina

	#libraryId	experimentId	platform	SRSId	anatId	anatName	cellTypeId	cellTypeName	stageId	stageName	url_GSM	infoOrgan	infoCellType_abInitio	infoStage	anatAnnotationStatus	cellTypeAnnotationStatus	stageAnnotationStatus	sex	strain	genotype	speciesId	RNAseqTags	protocol	protocolType	lib_name	sampleName	comment	annotatorId	lastModificationDate
58250	SRX902551	SRP055882	Illumina HiSeq 1500	SRS865236	UBERON:0019249	2-cell stage embryo	CL:0000353	blastoderm cell	MmusDv:0000005	Theiler stage 02	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	Preimplantation embryo: 2-cell	2-cell	2-cell (39-42h)	perfect match	perfect match	missing child term	NA	C57BL/6N X DBA/2N		10090	scRNA-seq	Smart-Seq2	Full-length	RNA-Seq 2-cell rep1	SAMN03389625,GSM1625862		SAC	2024-10-22
58251	SRX902550	SRP055882	Illumina HiSeq 1500	SRS865235	CL:0000365	animal zygote	CL:0000365	animal zygote	MmusDv:0000003	Theiler stage 01	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	Preimplantation embryo: Zygote	Zygote	Zygote	perfect match	perfect match	perfect match	NA	C57BL/6N X DBA/2N		10090	scRNA-seq	Smart-Seq2	Full-length	RNA-Seq zygote rep2	SAMN03389636,GSM1625861		SAC	2024-10-22
58252	SRX902549	SRP055882	Illumina HiSeq 1500	SRS865237	CL:0000365	animal zygote	CL:0000365	animal zygote	MmusDv:0000003	Theiler stage 01	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	Preimplantation embryo: Zygote	Zygote	Zygote	perfect match	perfect match	perfect match	NA	C57BL/6N X DBA/2N		10090	scRNA-seq	Smart-Seq2	Full-length	RNA-Seq zygote rep1	SAMN03389635,GSM1625860		SAC	2024-10-22
58253	SRX21819804	SRP461573	Illumina NovaSeq 6000	SRS18920590	UBERON:0000966	retina			MmusDv:0000163	17-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 120	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	RGC_live_AC	SAMN37446807	CD90.2 enrichment, not clear if platform is 10...	SAC	2024-12-12
58254	SRX21819803	SRP461573	Illumina NovaSeq 6000	SRS18920589	UBERON:0000966	retina			MmusDv:0000163	17-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 120	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	RGC_3_AC	SAMN37446808	CD90.2 enrichment, not clear if platform is 10...	SAC	2024-12-12
58255	SRX21819802	SRP461573	Illumina NovaSeq 6000	SRS18920588	UBERON:0000966	retina			MmusDv:0000163	17-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 120	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x_retina_WT_4M reaction 2	SAMN37446809	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12
58256	SRX21819801	SRP461573	Illumina NovaSeq 6000	SRS18920591	UBERON:0000966	retina			MmusDv:0000163	17-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 120	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x_retina_WT_4M reaction 1	SAMN37446810	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12
58257	SRX21819800	SRP461573	Illumina NovaSeq 6000	SRS18920587	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x_retina0401CD73Nv3	SAMN37446811	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58258	SRX21819799	SRP461573	Illumina NovaSeq 6000	SRS18920586	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x_retina0315CD73Nv3	SAMN37446812	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58259	SRX21819798	SRP461573	Illumina NovaSeq 6000	SRS18920585	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	10x_retina0315CD73Nv2	SAMN37446813	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58260	SRX21819797	SRP461573	Illumina NovaSeq 6000	SRS18920584	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	10x_retina0315CD73NDRv2 reaction 5	SAMN37446814	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58261	SRX21819796	SRP461573	Illumina NovaSeq 6000	SRS18920582	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	10x_retina0315CD73NDRv2 reaction 4	SAMN37446815	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58262	SRX21819795	SRP461573	Illumina NovaSeq 6000	SRS18920583	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	10x_retina0315CD73NDRv2 reaction 3	SAMN37446816	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58263	SRX21819794	SRP461573	Illumina NovaSeq 6000	SRS18920581	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	10x_retina0315CD73NDRv2 reaction 2	SAMN37446817	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58264	SRX21819793	SRP461573	Illumina NovaSeq 6000	SRS18920580	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	10x_retina0315CD73NDRv2 reaction 1	SAMN37446818	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58265	SRX21819792	SRP461573	Illumina NovaSeq 6000	SRS18920579	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x_mouse_CD90	SAMN37446819	CD90.2 enrichment, not clear if platform is 10...	SAC	2024-12-12
58266	SRX21819791	SRP461573	Illumina NovaSeq 6000	SRS18920578	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x_Retina0426Cd73N	SAMN37446820	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58267	SRX21819790	SRP461573	Illumina NovaSeq 6000	SRS18920576	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x_Retina0423Cd73N	SAMN37446821	CD73 enrichment, not clear if platform is 10X ...	SAC	2024-12-12
58268	SRX21819789	SRP461573	Illumina NovaSeq 6000	SRS18920575	UBERON:0000966	retina			MmusDv:0000154	8-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 56	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V2	3'end	10x_Retina0313v2	SAMN37446822	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12
58269	SRX21819788	SRP461573	Illumina NovaSeq 6000	SRS18920574	UBERON:0000966	retina			MmusDv:0000141	2-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 17	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x3_Ms_WT_PBS_2L	SAMN37446823	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12
58270	SRX21819787	SRP461573	Illumina NovaSeq 6000	SRS18920577	UBERON:0000966	retina			MmusDv:0000158	12-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 90	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x3_Ms_WT_P90	SAMN37446824	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12
58271	SRX21819786	SRP461573	Illumina NovaSeq 6000	SRS18920572	UBERON:0000966	retina			MmusDv:0000150	5-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 40	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x3_Ms_WT_P40	SAMN37446825	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12
58272	SRX21819785	SRP461573	Illumina NovaSeq 6000	SRS18920573	UBERON:0000966	retina			MmusDv:0000171	25-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 180	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x3_Ms_WT_P180 reaction 2	SAMN37446826	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12
58273	SRX21819784	SRP461573	Illumina NovaSeq 6000	SRS18920570	UBERON:0000966	retina			MmusDv:0000171	25-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 180	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x3_Ms_WT_P180 reaction 1	SAMN37446827	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12
58274	SRX21819783	SRP461573	Illumina NovaSeq 6000	SRS18920571	UBERON:0000966	retina			MmusDv:0000141	2-week-old stage	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi...	retina		Postnatal day 14	perfect match		missing child term	M	C57BL/6J	wild type	10090	scRNA-seq	10X Genomics V3	3'end	10x3_Ms_WT_P14	SAMN37446828	No enrichment, not clear if platform is 10X v2...	SAC	2024-12-12

	#experimentId	experimentName	experimentDescription	experimentSource	experimentStatus	RNAseqTags	numberOfAnnotatedLibraries	protocol	protocolType	GSE	Bioproject	PMID	reference_url	DOI	xrefs	comment
100	SRP125125	RNA-Seq profiling of 29 immune cell types and ...	We performed RNA-Seq transcriptome profiling o...	SRA	total	scRNA-seq	127 libraries	Adapted Smart-Seq2	Full-length	GSE107011	PRJNA418779	30726743	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6...	10.1016/j.celrep.2019.01.041	30528453[PMID]	NTR to check for annotation improvement, see h...
101	SRP356459	Molecular atlas of the human brain vasculature...	Molecular atlas of the human brain vasculature...	SRA	partial	scRNA-seq	27	10X Genomics V2	3'end	GSE256490	PRJNA800024	38987604	https://www.nature.com/articles/s41586-024-074...	10.1038/s41586-024-07493-y		GEO says 10X Genomics V2, supplemental methods...
102	SRP491411	Single-cell atlas of the human brain vasculatu...	A broad range of brain pathologies critically ...	SRA	partial	scRNA-seq	11	10X Genomics V2	3'end	GSE256491	PRJNA1079775	38987604	https://www.nature.com/articles/s41586-024-074...	10.1038/s41586-024-07493-y		GEO says 10X Genomics V2, supplemental methods...
103	SRP055882	The landscape of accessible chromatin in mamma...	The landscape of accessible chromatin in mamma...	SRA	partial	scRNA-seq	22	Smart-Seq2	Full-length	GSE66582	PRJNA277361	27309802	https://www.nature.com/articles/nature18606	10.1038/nature18606		partial - removed cell culture and siRNA knock...
104	SRP461573	A unified single cell atlas of the mouse retina	Single cell RNA sequencing (scRNA-seq) has adv...	SRA	total	scRNA-seq	22	10X Genomics V2, 10X Genomics V3	3'end	GSE243413	PRJNA1018454	38812536	https://pmc.ncbi.nlm.nih.gov/articles/PMC11134...	10.1016/j.isci.2024.109916	38328114[PMID]	not clear if platform is 10X v2 or v3 but anno...

	barcode	library	experiment	tissue	cell_type	cellTypeId	cellTypeName	cellTypeAnnotationStatus	name_Library
0	AAACCCAAGGGATCTG	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
1	AAACCCACATGGATCT	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
2	AAAGTCCAGCTGAAGC	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
3	AAATGGAGTCACCCTT	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
4	AACACACCAGAACTAA	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
5	AACAGGGAGTCCCGGT	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
6	AACAGGGGTCACATTG	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
7	AACCTTTTCCAGCCTT	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
8	AACGTCAGTTGTGGCC	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
9	AAGAACATCTCATGGA	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
10	AAGACTCGTATTTCTC	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
11	AAGCCATAGGGCCAAT	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
12	AAGTTCGAGGTCGACA	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
13	AAGTTCGCACTCTGCT	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
14	AAGTTCGTCCGTAGTA	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
15	AATGAAGGTCAGTCGC	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
16	AATGCCAAGTAAGGGA	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
17	ACAAAGAGTCTCTCTG	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
18	ACAACCAGTGTCTTGA	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14
19	ACAAGCTAGGTAGCCA	SRX21819783	SRP461573	retina	RBC	CL:0000751	rod bipolar cell	perfect match	10x3_Ms_WT_P14